Async API

The asynchronous polling-style API enables easy integration of long duration workflows, particularly video generation. Unlike the synchronous /v2/job endpoint which blocks until completion, the async API returns immediately with a job ID that you can poll to check progress and retrieve outputs.

Caution

This API is still in beta!

Endpoints

POST /v2/job/async Create Async Job

Creates a new async job and returns immediately with the job metadata. The job will be processed in the background.

Request: Same as synchronous /v2/job - supports both application/json and multipart/form-data content types.

Response: 201 Created with the job JSON containing the job id.

Note

Not all job types support async execution. If a job type doesn’t permit async, you’ll receive a 400 Bad Request with a message indicating you should use the sync API instead.

GET /v2/job/async/:id/job.state.current Get Job State

Returns the current state of the job as plain text. Use this for efficient polling.

States:

• processing - Job is currently being processed
• processed - Job completed successfully
• failed - Job encountered an error

Note

Async jobs use the state processed (not completed) when successful. This differs from the synchronous API which uses completed.

GET /v2/job/async/:id/job.json Get Job Metadata

Returns the full job JSON including configuration, timestamps, metrics, and error information (if failed).

GET /v2/job/async/:id/output List Output Files

Returns a list of output files produced by the job.

GET /v2/job/async/:id/output/:filename Download Output

Downloads a specific output file (e.g., video.mp4).

Status Codes

Code	Description
201	Job created successfully (POST /v2/job/async)
200	Request successful (GET endpoints)
400	Bad request - invalid job configuration or job type doesn’t support async
401	Unauthorized - missing or invalid authentication
404	Job not found or expired
429	Too many requests - exceeded async job limit or no capacity

Example

requests

Create the following main.py

main.py

import json
import os
import sys
import time

import requests
from requests.adapters import HTTPAdapter, Retry

prodia_token = os.getenv('PRODIA_TOKEN')
prodia_url = 'https://inference.prodia.com/v2/job/async'

session = requests.Session()
retries = Retry(allowed_methods=None, status_forcelist=Retry.RETRY_AFTER_STATUS_CODES)
session.mount('http://', HTTPAdapter(max_retries=retries))
session.mount('https://', HTTPAdapter(max_retries=retries))
session.headers.update({'Authorization': f"Bearer {prodia_token}"})

headers = {
    'Accept': 'video/mp4',
}

job = json.loads('''{
  "type": "inference.veo.fast.txt2vid.v1",
  "config": {
    "prompt": "Running in the woods with a dog.",
    "aspect_ratio": "16:9",
    "resolution": "720p",
    "generate_audio": true
  }
}''')

res = session.post(prodia_url, headers=headers, json=job)
print(f"Request ID: {res.headers['x-request-id']}")
print(f"Status: {res.status_code}")

if res.status_code != 201:
    print(res.text)
    sys.exit(1)

job = res.json()
job_id = job['id']
job_status = job['state']['current']
print(f"Job ID: {job_id}")
print(f"Job Status: {job_status}")

while job_status == 'processing':
    time.sleep(1)
    res = session.get(f"{prodia_url}/{job_id}/job.state.current")
    if res.status_code != 200:
        print(res.text)
        sys.exit(1)
    job_status = res.text
    print(f"Job Status: {job_status}")

if job_status != 'processed':
    res = session.get(f"{prodia_url}/{job_id}/job.json")
    if res.status_code != 200:
        print(res.text)
        sys.exit(1)
    print(res.json())
    sys.exit(1)

res = session.get(f"{prodia_url}/{job_id}/output/video.mp4")
if res.status_code != 200:
    print(res.text)
    sys.exit(1)

with open('output.mp4', 'wb') as f:
    f.write(res.content)

print('Output file: output.mp4')

axios

Create the following main.js

main.js

const axios = require('axios');
const axiosRetry = require('axios-retry').default;
const fs = require('node:fs');

async function main() {
    axiosRetry(axios, {
        retries: 3,
        retryCondition: (error) => {
            return [413, 429, 503].includes(error.response.status);
        },
    });

    let job = {
      "type": "inference.veo.fast.txt2vid.v1",
      "config": {
        "prompt": "Running in the woods with a dog.",
        "aspect_ratio": "16:9",
        "resolution": "720p",
        "generate_audio": true
      }
    };

    let res = await axios({
        method: 'POST',
        url: 'https://inference.prodia.com/v2/job/async',
        headers: {
            'Accept': 'video/mp4',
            'Authorization': `Bearer ${process.env.PRODIA_TOKEN}`,
        },
        data: job,
    });

    job = res.data;
    let jobStatus = job.state.current;
    console.log(`Job ID: ${job.id}`);
    console.log(`Job Status: ${jobStatus}`);

    while (jobStatus == 'processing') {
        await new Promise(resolve => setTimeout(resolve, 1000));
        res = await axios({
            method: 'GET',
            url: `https://inference.prodia.com/v2/job/async/${job.id}/job.state.current`,
            headers: {
                'Authorization': `Bearer ${process.env.PRODIA_TOKEN}`,
            },
        });
        jobStatus = res.data;
        console.log(`Job Status: ${jobStatus}`)
    }

    if (jobStatus != 'processed') {
        console.log(job);
        process.exit(1);
    }

    res = await axios({
        method: 'GET',
        url: `https://inference.prodia.com/v2/job/async/${job.id}/output/video.mp4`,
        headers: {
            'Authorization': `Bearer ${process.env.PRODIA_TOKEN}`,
        },
        responseType: 'arraybuffer',
    });

    fs.writeFileSync('output.mp4', res.data);
    console.log('Output file: output.mp4');
}

await main();

Note

Outputs are only available for 1 hour.